1. Field of the Invention
The present invention relates to optical signal processing using electron trapping materials and, more specifically, to the use of electron trapping materials in a compact optical vector-matrix multiplier system.
2. Description of the Related Art
The capabilities of electron trapping materials having been demonstrated in various disciplines of optical signal processing. For example, the application of electron trapping materials to parallel Boolean logic has been reported by S. Jutamulia, G. M. Storti, J. Lindmayer, and W. Seiderman in "Application of Electron trapping (ET) Materials to Optical Parallel Logic Processing," Proc. SPIE. 1151, 83, 1989. The use of electron trapping materials in memory devices has been demonstrated by S. Jutamulia, J. Lindmayer, and G. Storti in "Optical Pattern Recognition and Associative Memory Using Electron trapping Materials," Proc. SPIE 1053, 67, 1989. Recently, the capabilities of electron trapping materials applied to Hopfield type neural networks has been discussed by S. Jutamulia, G. M. Storti, J. Lindmayer, W. Seiderman in "Optical Neural Nelectron trappingwork Digital Multi-Value Processor with Learning Capability Using Electron trapping Materials," Proc. SPIE 1215, 457, 1990.
A neural network model is basically represented by a matrix-vector multiplication. J. J. Hopfield, "Neural Networks and Physical Systems with Emergent Collective Computational Abilities", Proc. Natl. Acad. Sci. USA, 79, 2554-2558 (1982). Vector-matrix multiplication can be performed optically by converting the vector into matrix form, forming an image of that matrix, and optically multiplying that image with the image of a vector. The conversion of a vector into a matrix is accomplished by the following interconnection matrix T.sub.ij : ##EQU1## where V.sub.i and V.sub.j are the ith and jth elements of the vector, and where i and j represent the row and column of the matrix elements.
For example, the vector (1,0,0,1,1) will convert into the matrix: ##EQU2##
Electron trapping materials are useful in performing optical multiplications. As described in A. D. McAulay, "Optical Orthogonal Neural Network Associative Memory with Luminescent Rebroadcasting Devices," Int. Joint Conf. Neu. Net. IEEE--89CH2765--G, Volume III, 483-485 (1985), multiplication can be performed by writing one image, say A, onto an electron trapping material using visible light, and then reading with IR light in a pattern representing the second image B. The output luminescent at each pixel position is proportional to the analog product of the read intensity at that pixel and the stored value at that pixel.
While the prior techniques for optical vector-matrix multiplication such as disclosed by McAulay have been successfully demonstrated, they use fan-out and fan-in lenses and thus require precise optical alignment and take up a considerable amount of space. Accordingly, optical vector-matrix multiplication has been limited to laboratory bench top systems. Thus, a need exists for a vector-matrix multiplier which is compact, rugged and which can actually be implemented in an optical computer.